Routing issues and challenges in Underwater Wireless Sensor Networks

Sarao, Pushpender; Chattu, Kannaiah; Ch, Swapna

doi:10.26438/ijcse/v6i2.238241

Cited by 4 publications

(2 citation statements)

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“…The clustering and routing algorithms of WSNs cannot directly apply to UWSNs due to acoustic signals and different layers of communications. Thus, designing either clustering-based or route formation algorithms by considering the ocean properties of UWSNs gained significant attention from researchers [18][19][20][21]. But UWSNs challenges mainly related achieve trade-off among energy-efficient, higher PDR, and minimum communication delay parameters.…”

Section: Introductionmentioning

confidence: 99%

Energy optimization using swarm intelligence for IoT-Authorized underwater wireless sensor networks

Gavali

Kadam²,

Patil³

2022

Microprocessors and Microsystems

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Section: Introductionmentioning

confidence: 99%

Energy optimization using swarm intelligence for IoT-Authorized underwater wireless sensor networks

Gavali

Kadam²,

Patil³

2022

Microprocessors and Microsystems

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Section: Introductionmentioning

confidence: 99%

Energy Optimization using Swarm Intelligence for IoT-Authorized Underwater Wireless Sensor Networks

Gavali¹,

Vaze

Ubale

2021

Preprint

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The technology advancement in the Internet of Things (IoT) enables a variety of smart monitoring applications assisted by networks like Wireless Sensor Networks (WSNs) and Underwater WSNs (UWSNs). The IoT-UWSNs supported a wide range of applications such as underwater data collection, underwater equipment monitoring, underwater imaging, etc. The acoustic signals have been utilized for communication in IoT-UWSNs over radio signals and optical signals. Data transmission using acoustic signals is suffering from lower throughput, excessive energy consumption, long transmission delay, and lower network lifetime. Several data forwarding and clustering algorithms have recently been proposed to enhance UWSN's performances. This paper proposed a novel routing solution for energy and QoS-efficient data transmission from the underwater sensor node to the surface sink using Swarm Intelligence (SI). This protocol called Energy Optimization using Routing Optimization (EORO) protocol. To optimize the UWSNs performance, we used Effective Fitness Function-based Particle Swarm Optimization (EFF-PSO) to select the best forwarder node for data transmission. In EORO, forwarding relay nodes discovered by the intended source node using location information firstly. Then EFF-PSO algorithm is applied to select the optimal relay node considering the rich set of parameters. Four parameters of each forwarder node used for fitness computation as residual energy, packet transmission ability, node connectivity, and distance. These parameters are intelligently selected to avoid packet collisions to achieve energy consumption and delay reduction with higher throughput. An experimental result shows that the EORO protocol outperformed underlying routing techniques using throughput, energy consumption, delay, and Packet Delivery Ratio (PDR).

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Enhanced Link Quality-based Routing Protocol for underwater networks

Waghmare,

Chandavarkar

2023

2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)

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Routing issues and challenges in Underwater Wireless Sensor Networks

Cited by 4 publications

References 0 publications

Energy optimization using swarm intelligence for IoT-Authorized underwater wireless sensor networks

Energy optimization using swarm intelligence for IoT-Authorized underwater wireless sensor networks

Energy Optimization using Swarm Intelligence for IoT-Authorized Underwater Wireless Sensor Networks

Enhanced Link Quality-based Routing Protocol for underwater networks

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